1. Field of the Invention
This invention relates generally to signal correlation and, more particularly, to the use of correlation techniques for image recognition.
2. Description of the Prior Art
Correlation techniques are useful in a variety of signal processing applications. As one example, signal correlation of radar return signals utilizing set delays can provide target detection and effective improvement of signal-to-noise ratio for return signals having average noise levels substantially greater than the signal level. A specialized variation of such techniques is disclosed in Mitchell U.S. Pat. No. 3,237,160 which involves correlation to identify a special code word form of data transmission.
Similar correlation systems for operating on radar signals are disclosed in Bailey U.S. Pat. No. 3,887,918, Wilmot U.S. Pat. No. 4,031,364 and Debuisser U.S. Pat. No. 4,156,876. Similarly, the digital delay line correlator of Harrison et al U.S. Pat. No. 3,947,672 is used in radar systems, among others, for detection of pulse repetition interval for a series of time spaced signal pulses.
The Schmitt U.S. Pat. No. 3,604,911 describes a digital correlator for measuring the extent of agreement between two distinct binary sequences of signals. The correlator there described utilizes a plurality of segment comparators respectively operating on the bits within the selected segments of the sequences of predetermined length.
Other fields of use involve data transmission in which identification of pre-existing transmitted codes or the comparison of two or more signals is performed for synchronization purposes or the like. Examples of such applications of signal correlation techniques are found in Dupraz et al U.S. Pat. No. 3,463,911, Jordan et al U.S. Pat. No. 3,947,673 and Gutleber et al U.S. Pat. No. 3,955,197.
Signal correlation may also be useful in systems for automatically comparing signals derived from aerial photographs to detect changes in photographs taken at different times, such as are important in spotting movements of troops or vehicles, the erection of military installations, and the like. A system which may be used for this purpose is disclosed in the Marsh U.S. Pat. No. 4,164,728.
An auto-correlation function method and apparatus are disclosed in Grandchamp U.S. Pat. No. 4,158,234 as used for determining the size of particles in Brownian motion.
When comparing two images taken at different times or from different systems, one is generally faced with problems relating to contrast differences, average intensity differences and noise. Contrast differences can be caused by changes in system gains, while average intensity differences can result from changes in light intensity and noise is usually of the electronic additive type.
The standard algorithm for comparing a reference D and an image C is EQU F(C,D)=(C.multidot.D/.vertline.C.vertline..vertline.D.vertline.) (1)
where "." denotes the dot product and the reference D and image C are treated as vectors. Direct implementation of this function, however, requires division which is difficult to accomplish at real time rates using a cost effective hardware implementation. If the components of C and D are restricted to 1 and 0, then this approach is similar to that which is the subject of the Hogan et al U.S. Pat. No. 4,244,029 where the disclosed correlation function is the mean absolute difference (MAD).